Over the long term, this metric shows how many Job Function Email Database users on average have reached your website through a particular campaign or channel. So this is an ideal KPI that you can use to assess your branding. See the big differences between campaigns in the example below. For example, you can see here that the 'Brandname Ad-rotation' campaign has a Job Function Email Database high revenue per user (LTV). Example with brandname ad-rotation. Simulate a different attribution model with the Model Comparison Tool Google Analytics (still) uses a Job Function Email Database model in which conversions and transactions are allocated on the basis of 'last non-direct click.
That is, the channel that delivers the last Job Function Email Database click in the customer journey (except direct traffic) gets the conversion. Not really a useful piece of information to qualify your branding traffic. Since branding mainly ensures a broad influx of users, who are often still in the exploratory phase of a purchase process and therefore not only in the decision phase. You can simulate a dJob Function Email Database ifferent attribution model via the Model Comparison Tool of Google Analytics. In this way, you temporarily move away from the 'last non-direct click' model and you see how channels are assessed with different attribution rules. Of course, it depends on your own marketing Job Function Email Database strategy and vision of what you mean by branded traffic.
A logical hypothesis could be In Job Function Email Database order to properly assess my branded traffic, I give every step in the customer journey the same value”. In this way, you not only look at the last channel that scores the conversion but also at the Job Function Email Database channels that are higher or halfway in the funnel. In the report below I compare the linear model with the last non-direct click model. This means: do not give the channel all the Job Function Email Database credits at the end of the customer journey but divide the credits at overall touchpoints.